In some situations, various messages are each distributed to an appropriate distribution destination out of multiple distribution destinations according to the content of the message. For instance, a known technique calculates, for each distribution destination of multiple distribution destinations, a probability that a message to be distributed is distributed to each distribution destination, based on co-occurrence probability information that stores a co-occurrence probability of each word of multiple words in association with each distribution destination of the multiple distribution destinations, and determines that a distribution destination with the highest calculated probability is an appropriate distribution destination. This technique is called Bayesian classification.
In related art, a server at a transfer destination of a message, which has been inputted using the Bayesian classification, is determined based on given learning data, for instance. Also, a known technique generates, by using the Bayesian estimation, a prior distribution of the number of occurrences of each word included in a second vocabulary set, based on first word distribution that is a multinomial distribution of the number of occurrences of each word included in a first vocabulary set.
Related techniques are disclosed in, for example, Japanese Laid-open Patent Publication Nos. 2015-153250 and 2013-69140.